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Everything you need to know about Artificial Intelligence (AI)
Artificial intelligence (AI) is the ability of a computer or a computer-controlled robot to accomplish tasks that would normally be performed by intelligent beings. The phrase also can refer to any machine that demonstrates human-like characteristics like learning and problem-solving. The ability of artificial intelligence to rationalize and execute actions that have the best likelihood of reaching a certain goal is its ideal feature.
It was proved in the 1940s that computers can be programmed to perform extremely difficult jobs, such as finding proofs for mathematical theorems or playing chess. Some programs have surpassed the performance levels of human specialists and professionals in executing specified activities, indicating that artificial intelligence can be present in applications in a limited sense.
Milestones on AI in Early Stage
First AI Program
Christopher Strachey, wrote the first effective AI program in 1951: At an acceptable speed, this software could play a whole game of checkers. In 1952, information on the first effective demonstration of machine learning was made public.
The employment of some automated approach of producing and assessing consecutive “generations” of a program until a highly proficient solution arises is typical of evolutionary computing.
A theorem-proving program built by Allen Newell and J. Clifford Shaw in 1955–56, the Logic Theorist, as the program was called, was created to verify theorems from the British philosopher-mathematicians’ Principia Mathematical (1910–13), a three-volume book published between 1910 and 1913.
AI Programming Language
Newell, Simon, and Shaw developed their Information Processing Language (IPL), a computer language suited for AI programming while working on the Logic Theorist and GPS. IPL was built on a very flexible data structure known as a list. In 1960, John McCarthy combined aspects of IPL with the lambda calculus (a formal mathematical-logical framework) to create LISP (List Processor), which is still the most widely used AI programming language in the United States.
Categories of Artificial Intelligence Explained
Narrow or Weak Artificial Intelligence
Weak AI encapsulates a system created to do a specific task. NAI is a phrase used to describe artificial intelligence systems that are designed to perform a specific or limited task. When a machine can execute a given task better than a human, it is considered to have narrow artificial intelligence.
Spam email filtering, music recommendation services, and even driverless vehicles could all benefit from narrow AI. Video games, such as the chess example above, and personal assistants, Alexa and Siri, are examples of weak AI systems.
General or Strong Artificial Intelligence
Strong AI are machines that do jobs that are similar to those performed by humans. These are typically more sophisticated and difficult systems. They are programmed to deal with scenarios in which they may be required to solve problems without the assistance of a human.
AGI allows a machine to use knowledge and skills in a variety of situations. By allowing for independent learning and problem-solving, this more closely resembles human intelligence.
Artificial Super Intelligence (ASI)
ASI does more than mimic or understands human intelligence and behavior; ASI is when computers become self-aware and outperform human intelligence and capability.
Artificial Super Intelligence can make everything better than we do like science, math’s, sports, arts, medicine, hobbies and more.
Types of Artificial Intelligence
Machine Learning: Machine learning is a branch of AI that allows computers to find and improve on their own without having to be explicitly programmed. Machine learning is concerned with the creation of computer programs that can access data and learn on their own.
Machine learning allows for the examination of large amounts of data. While it generally provides faster, more accurate results in identifying profitable possibilities or risky threats, fully training it may take more time and resources.
Deep Learning: Deep learning is an area of machine learning that deals with artificial neural networks, which are algorithms inspired by the structure and function of the brain.
Deep learning is an artificial intelligence subset of machine learning that uses neural networks to learn unsupervised from unstructured or unlabeled data.
Top Applications of AI in 2020
● Google Maps (AI-powered)
● Spam filters on mails
● Facial Recognition
● Voice-to-text features
● Search recommendations
● Fraud prevention and protection
Future of AI
AI is evolving at a rapid pace, with breakthroughs and milestones being announced regularly. Artificial Intelligence has emerged as the single most significant technological advancement. An AI certification will provide you with an advantage over other industry participants.
AI has the potential to multitask, recall and memorize knowledge flawlessly, operate without interruption, perform calculations at lightning speed, filter through vast records and papers, and make unbiased judgments.
Artificial intelligence is the science of teaching machines to perform tasks that are similar to or identical to those performed by humans. AI is the newest cutting-edge technology. VC firms are pouring billions of dollars into companies and AI projects.
It gets tough to manage the rules as a system becomes more complicated. To solve this problem, the machine can use data to learn how to handle all of the possibilities that may arise in a particular environment.
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